From 1d739fef11699bcd8821c4d08a5958637b8d9eca Mon Sep 17 00:00:00 2001 From: Chris Donnay Date: Wed, 18 Sep 2024 12:54:25 -0400 Subject: [PATCH] delete unnecessary files --- notebooks/6_gerrychain.ipynb | 163 - notebooks/PA_VTDs.json | 692797 -------------------------------- notebooks/borda_results.json | 1 - 3 files changed, 692961 deletions(-) delete mode 100644 notebooks/6_gerrychain.ipynb delete mode 100644 notebooks/PA_VTDs.json delete mode 100644 notebooks/borda_results.json diff --git a/notebooks/6_gerrychain.ipynb b/notebooks/6_gerrychain.ipynb deleted file mode 100644 index 621db07..0000000 --- a/notebooks/6_gerrychain.ipynb +++ /dev/null @@ -1,163 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Gerrychain\n", - "MGGG also maintains a package called `gerrychain`, which is used to draw legislative districts. One common pipeline that we use in the lab is to generate a large number of possible maps using `gerrychain`, and then for each district in each map, use VoteKit to understand possible election outcomes. This section of the tutorial provides a short example of how this might be done." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To learn how to use gerrychain, please visit https://mggg.github.io/GerryChain/index.html\n", - "\n", - "You will need to run `pip install 'gerrychain[geo]'` in your terminal with your virtual environment activated." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# TODO download a json for pennsylvania\n", - "https://github.com/mggg/GerryChain/blob/main/docs/_static/PA_VTDs.json" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will use the 2016 Presidential race in Pennsylvania to estimate the number of Republicans and Democrats in each district in the map. To start, we run gerrychain to generate a large number of plans with four districts. Again, don't worry about the implementation details of gerrychain here." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "from gerrychain import (GeographicPartition, Partition, Graph, MarkovChain,\n", - " proposals, updaters, constraints, accept, Election)\n", - "from gerrychain.proposals import recom\n", - "from functools import partial\n", - "import pandas\n", - "\n", - "NUM_DISTRICTS = 4\n", - "graph = Graph.from_json(\"./PA_VTDs.json\")\n", - "\n", - "# Population updater, for computing how close to equality the district\n", - "# populations are. \"TOTPOP\" is the population column from our shapefile.\n", - "my_updaters = {\"population\": updaters.Tally(\"TOT_POP\", alias=\"population\")}\n", - "\n", - "# Election updaters, for computing election results using the vote totals\n", - "# from our shapefile.\n", - "\n", - "elections = [\n", - " Election(\"PRES16\", {\"Democratic\": \"T16PRESD\", \"Republican\": \"T16PRESR\"})\n", - "]\n", - "\n", - "election_updaters = {election.name: election for election in elections}\n", - "my_updaters.update(election_updaters)\n", - "\n", - "# we use a random plan with 4 districts\n", - "initial_partition = Partition.from_random_assignment(\n", - " graph,\n", - " n_parts = NUM_DISTRICTS,\n", - " epsilon = .02,\n", - " pop_col=\"TOT_POP\",\n", - " updaters=my_updaters\n", - ")\n", - "\n", - "# The ReCom proposal needs to know the ideal population for the districts so that\n", - "# we can improve speed by bailing early on unbalanced partitions.\n", - "\n", - "ideal_population = sum(initial_partition[\"population\"].values()) / len(initial_partition)\n", - "\n", - "# We use functools.partial to bind the extra parameters (pop_col, pop_target, epsilon, node_repeats)\n", - "# of the recom proposal.\n", - "proposal = partial(\n", - " recom,\n", - " pop_col=\"TOT_POP\",\n", - " pop_target=ideal_population,\n", - " epsilon=0.02,\n", - " node_repeats=2\n", - ")\n", - "\n", - "\n", - "pop_constraint = constraints.within_percent_of_ideal_population(initial_partition, 0.02)\n", - "\n", - "chain = MarkovChain(\n", - " proposal=proposal,\n", - " constraints=[\n", - " pop_constraint\n", - " ],\n", - " accept=accept.always_accept,\n", - " initial_state=initial_partition,\n", - " total_steps=100\n", - ")\n", - "\n", - "# This might take a minute.\n", - "# store the democrat and republican vote totals\n", - "data = pandas.DataFrame(\n", - " [partition[\"PRES16\"].counts(\"Democratic\") + partition[\"PRES16\"].counts(\"Republican\")\n", - " for partition in chain], \n", - " columns = [f\"D_{i}_Dem\" for i in range(len(initial_partition))] + \\\n", - " [f\"D_{i}_Rep\" for i in range(len(initial_partition))]\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now for each district in each map (4 x 100), we ask VoteKit to simulate an STV election where each district elects 4 candidates. We compute the number of Republican candidates who won, and display this for three different models of ballot generator using an area plot." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import votekit.ballot_generator as bg\n", - "\n", - "\n", - "\n", - "for map_num, row in data.iterrows():\n", - "\n", - " for district in range(NUM_DISTRICTS):\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/PA_VTDs.json b/notebooks/PA_VTDs.json deleted file mode 100644 index 691f4ee..0000000 --- a/notebooks/PA_VTDs.json +++ /dev/null @@ -1,692797 +0,0 @@ -{ - "directed": false, - "multigraph": false, - "graph": [ - [ - "crs", - "{\"$schema\":\"https://proj.org/schemas/v0.4/projjson.schema.json\",\"type\":\"GeographicCRS\",\"name\":\"NAD83\",\"datum\":{\"type\":\"GeodeticReferenceFrame\",\"name\":\"North American Datum 1983\",\"ellipsoid\":{\"name\":\"GRS 1980\",\"semi_major_axis\":6378137,\"inverse_flattening\":298.257222101}},\"coordinate_system\":{\"subtype\":\"ellipsoidal\",\"axis\":[{\"name\":\"Geodetic latitude\",\"abbreviation\":\"Lat\",\"direction\":\"north\",\"unit\":\"degree\"},{\"name\":\"Geodetic longitude\",\"abbreviation\":\"Lon\",\"direction\":\"east\",\"unit\":\"degree\"}]},\"scope\":\"Geodesy.\",\"area\":\"North America - onshore and offshore: Canada - Alberta; British Columbia; Manitoba; New Brunswick; Newfoundland and Labrador; Northwest Territories; Nova Scotia; Nunavut; Ontario; Prince Edward Island; Quebec; Saskatchewan; Yukon. Puerto Rico. United States (USA) - Alabama; Alaska; Arizona; Arkansas; California; Colorado; Connecticut; Delaware; Florida; Georgia; Hawaii; Idaho; Illinois; Indiana; Iowa; Kansas; Kentucky; Louisiana; Maine; Maryland; Massachusetts; Michigan; Minnesota; Mississippi; Missouri; Montana; Nebraska; Nevada; New Hampshire; New Jersey; New Mexico; New York; North Carolina; North Dakota; Ohio; Oklahoma; Oregon; Pennsylvania; Rhode Island; South Carolina; South Dakota; Tennessee; Texas; Utah; Vermont; Virginia; Washington; West Virginia; Wisconsin; Wyoming. US Virgin Islands. British Virgin Islands.\",\"bbox\":{\"south_latitude\":14.92,\"west_longitude\":167.65,\"north_latitude\":86.46,\"east_longitude\":-47.74},\"id\":{\"authority\":\"EPSG\",\"code\":4269}}" - ] - ], - "nodes": [ - { - "boundary_node": false, - "area": 0.0063017857514999324, - "STATEFP10": "42", - "COUNTYFP10": "039", - "VTDST10": "60", - "GEOID10": "42039060", - "VTDI10": "A", - "NAME10": "CAMBRIDGE SPRINGS Voting District", - "NAMELSAD10": "CAMBRIDGE SPRINGS Voting District", - "LSAD10": "00", - "MTFCC10": "G5240", - "FUNCSTAT10": "N", - "ALAND10": 2258229, - "AWATER10": 0, - "INTPTLAT10": "+41.8018353", - "INTPTLON10": "-080.0596566", - "ATG12D": 0.0, - "ATG12R": 0.0, - "GOV10D": 0.0, - "GOV10R": 0.0, - "PRES12D": 0.0, - "PRES12O": 0.0, - "PRES12R": 0.0, - "SEN10D": 0.0, - "SEN10R": 0.0, - "T16ATGD": 0.0, - "T16ATGR": 0.0, - "T16PRESD": 0, - "T16PRESOTH": 0.0, - "T16PRESR": 0, - "T16SEND": 0, - "T16SENR": 0, - "USS12D": 0.0, - "USS12R": 0.0, - "GOV": 3, - "TS": 5, - "HISP_POP": 0, - "TOT_POP": 0, - "WHITE_POP": 0, - "BLACK_POP": 0, - "NATIVE_POP": 0, - "ASIAN_POP": 0, - "F2014GOVD": 1, - "F2014GOVR": 1, - "2011_PLA_1": 3, - "REMEDIAL_P": 14, - "538CPCT__1": 3, - "538DEM_PL": 3, - "538GOP_PL": 3, - "8THGRADE_1": 1, - "id": 0 - }, - { - "boundary_node": false, - "area": 0.01045703802000018, - "STATEFP10": "42", - "COUNTYFP10": "039", - "VTDST10": "510", - "GEOID10": "42039510", - "VTDI10": "A", - "NAME10": "TITUSVILLE WD 03", - "NAMELSAD10": "TITUSVILLE WD 03", - "LSAD10": "00", - "MTFCC10": "G5240", - "FUNCSTAT10": "N", - "ALAND10": 1367084, - "AWATER10": 0, - "INTPTLAT10": "+41.6221809", - "INTPTLON10": "-079.6806828", - "ATG12D": 1262.0, - "ATG12R": 1568.0, - "GOV10D": 634.0, - "GOV10R": 1365.0, - "PRES12D": 1248.0, - "PRES12O": 48.0, - "PRES12R": 1706.0, - "SEN10D": 723.0, - "SEN10R": 1297.0, - "T16ATGD": 1042.0, - "T16ATGR": 1995.0, - "T16PRESD": 902, - "T16PRESOTH": 126.0, - "T16PRESR": 1994, - "T16SEND": 921, - "T16SENR": 1999, - "USS12D": 1180.0, - "USS12R": 1739.0, - "GOV": 3, - 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